Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

Perceptron Mk1.5Perceptron Remove
Claude Sonnet 5.5Anthropic Remove
Gemini 3.5 TranscribeGoogle Remove
GLM 5.3 FlashZ.AI Remove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs claude-sonnet-5.5 vs gemini-3.5-transcribe vs glm-5.3-flash
Attribute	Perceptron Mk1.5perceptron-mk1.5	Claude Sonnet 5.5claude-sonnet-5.5	Gemini 3.5 Transcribegemini-3.5-transcribe	GLM 5.3 Flashglm-5.3-flash
Pricing
Input	$0.15 / 1M	$2.00 / 1M	— Not priced per input token	$0.075 / 1M
Output	$1.50 / 1M	$10.00 / 1M	— Not priced per output token	$0.25 / 1M
Cache Write (5m)	$0.15 / 1M	$2.50 / 1M	Not applicable	$0.075 / 1M
Cache Write (1h)	$0.15 / 1M	$4.00 / 1M	Not applicable	$0.075 / 1M
Cache Read	$0.15 / 1M	$0.10 / 1M	Not applicable	$0.075 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	36.9K	1M	98.3K	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	Yes	Yes	Yes
Function Calling	No	Yes	Yes	Yes
JSON Mode	No	Yes	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	Perceptron	Anthropic	Google	Z.AI
Category	chat	chat	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-25	—	2026-09-25	—
Description
Summary	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.